# A tibble: 150 × 33
episode title imdb_…¹ air_d…² air_d…³ air_d…⁴ air_d…⁵ seaso…⁶ seaso…⁷ seaso…⁸ seaso…⁹ seaso…˟
<dbl> <fct> <dbl> <int> <int> <int> <int> <dbl> <dbl> <dbl> <dbl> <dbl>
1 18 Last Day… 7.8 0 0 0 0 0 0 0 0 0
2 14 Vandalism 7.6 0 0 0 0 0 0 0 0 0
3 8 Performa… 8.2 0 0 0 0 1 0 0 0 0
4 5 Here Com… 7.1 0 0 0 0 0 0 0 0 0
5 22 Beach Ga… 9.1 0 0 0 0 0 1 0 0 0
6 1 Nepotism 8.4 0 0 0 0 0 0 0 0 0
7 15 Phyllis'… 8.3 0 0 0 0 0 1 0 0 0
8 21 Livin' t… 8.9 0 0 0 0 0 0 0 0 0
9 18 Promos 8 0 0 0 0 0 0 0 0 0
10 12 Pool Par… 8 0 0 0 0 0 0 0 0 0
# … with 140 more rows, 21 more variables: season_X7 <dbl>, season_X8 <dbl>, season_X9 <dbl>,
# air_date_dow_Mon <dbl>, air_date_dow_Tue <dbl>, air_date_dow_Wed <dbl>, air_date_dow_Thu <dbl>,
# air_date_dow_Fri <dbl>, air_date_dow_Sat <dbl>, air_date_month_Feb <dbl>,
# air_date_month_Mar <dbl>, air_date_month_Apr <dbl>, air_date_month_May <dbl>,
# air_date_month_Jun <dbl>, air_date_month_Jul <dbl>, air_date_month_Aug <dbl>,
# air_date_month_Sep <dbl>, air_date_month_Oct <dbl>, air_date_month_Nov <dbl>,
# air_date_month_Dec <dbl>, top10 <int>, and abbreviated variable names ¹imdb_rating, …